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Predictive Analytics using R and Java

Predictive Analytics using R and Java

Abhilshit Soni

Lead Engineer HERE

A full stack developer with 9 years of experience in designing and developing integrated enterprise applications that talk to each other and can be ac...cessed over the web browser as well as mobile devices. He works with HERE as a Lead Engineer, and is involved in next generation map making apps/tools development.

Description

Predictive analytics is about predicting future outcomes based on currently available or historical data using several machine learning algorithms and statistical techniques.

R - a language and environment for statistical computing, makes it really easy to quickly try out several algorithms like Decision Trees, Random Forests, Neural Networks etc. on top of your existing datasets. R packages, like Rattle, can quickly allow you to interactively create machine learning models which can be trained and exported to a PMML file format.

The Predictive Model Markup Language (PMML) is a platform agnostic, XML-based predictive model interchange format which can be used to exchange the trained machine learning models across different technology platforms. Any machine learning model exported in PMML can be imported in your Java program by using libraries like JPPML and can be used to predict future outcomes based on the existing data.

As part of this webinar, you will understand how to quickly create trained machine learning model based on an existing dataset, export it to a PMML file and import into a Java Project.